Peter Stone's Selected Publications

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Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems

Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems.
Stefano Albrecht and Peter Stone.
Artificial Intelligence, 258:66–95, Elsevier, 2018.
Available from the publisher's webpage and arXiv

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Abstract

Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other agents, by constructing models which make predictions about various properties of interest (such as actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now exist which vary widely in their methodology and underlying assumptions, catering to the needs of the different sub-communities within which they were developed and reflecting the different practical uses for which they are intended. The purpose of the present article is to provide a comprehensive survey of the salient modelling methods which can be found in the literature. The article concludes with a discussion of open problems which may form the basis for fruitful future research.

BibTeX Entry

@article{AIJ18-Albrecht,
  title = {Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems},
  author = {Stefano Albrecht and Peter Stone},
  journal = {Artificial Intelligence},
  volume = {258},
  pages = {66--95},
  year = {2018},
  publisher = {Elsevier},
  abstract = {
    Much research in artificial intelligence is concerned with the development of
      autonomous agents that can interact effectively with other agents. An important aspect of
      such agents is the ability to reason about the behaviours of other agents, by
      constructing models which make predictions about various properties of interest (such as
      actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now
      exist which vary widely in their methodology and underlying assumptions, catering to
      the needs of the different sub-communities within which they were developed and
      reflecting the different practical uses for which they are intended. The purpose of the
      present article is to provide a comprehensive survey of the salient modelling methods
      which can be found in the literature. The article concludes with a discussion of
      open problems which may form the basis for fruitful future research.},
  wwwnote={Available from the <a href="https://doi.org/10.1016/j.artint.2018.01.002">publisher's webpage</a> and <a href="https://arxiv.org/abs/1709.08071">arXiv</a>},
}

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